1 Introduction to R 2 The Tidyverse and Reproducible R Workflows 3 Descriptive Statistcs, Models, and Distributions 4 Introduction to the Linear Model " Simple Linear Regression 5 Correlation, Linear, and Nonlinear Transformations 6 Multiple Regression 7 Categorical Predictors 8 Interactions and Nonlinear Effects 9 Inferential Statistics 1 : Significance Testing 10 Inferential Statistics 2 : Issues in Significance Testing 11 Inferential Statistics 3: Significance Testing in a Regression Context 12 Generalized Linear Models 1 : Logistic Regression 13 Generalized Linear Models 2 : Poisson Regression 14 Mixed Models 1: Conceptual Introduction 15 Mixed Models 2 : Extended Example, Significance Testing, Convergence Issues 16 Outlook and Strategies for Model Building